個案資料

At a conference in November 2020, the chief executive officers (CEOs) of two exceptional healthcare start-ups—AliveCor Inc. (AliveCor) and Neurobit Inc. (Neurobit)—discussed their paths to innovation: AliveCor, a trailblazing health tech company, had emerged in 2011 with electrocardiogram (ECG) hardware and software that had since garnered global recognition. Neurobit, a digital health start-up, entered the scene in 2018 with sleep biomarker–based health analytics that could predict adverse cardiopulmonary or neurological outcomes. As the CEOs shared their stories, common challenges emerged regarding data acquisition, privacy concerns, and regulatory compliance. Amid their successes, the two companies experienced the necessity of addressing data challenges to achieve AI’s full potential in healthcare. They made trade-offs between time and resources amid a rapidly evolving industry and employed various strategies and solutions, from academic collaborations to extensive data collection, in their quest to determine the best strategy to use to overcome the challenges of efficiently and cost-effectively acquiring and utilizing data to drive innovation and gain a competitive edge.

This teaching case is designed for undergraduate and graduate students in fields such as healthcare management, business, entrepreneurship, health informatics, and data science. It is also suitable for executive education programs and workshops focusing on healthcare innovation, technology adoption, and AI applications in the medical domain. This case underscores the determination and innovation of two AI-based healthcare start-ups, driving home the potential of AI to reshape this sector. It invites students to explore the convergence of AI, healthcare, and entrepreneurship and encourages them to evaluate the complexities of data acquisition and ethical considerations while contemplating the dilemmas that start-ups grapple with. After working through the case and assignment questions, students will be able to do the following:<ul><li>Explain the significance of AI in healthcare and outline its potential to transform the industry by improving patient outcomes, diagnosis, and treatment.</li><li>Analyze the key challenges faced by healthcare start-ups, particularly those related to data acquisition and utilization for AI development.</li><li>Evaluate the strategies and solutions these start-ups adopt to overcome data-related hurdles and create competitive advantages.</li><li>Describe the dilemmas faced by contemporary digital health start-ups in terms of balancing time, resources, and competition in the fast-evolving AI healthcare sector.</li></ul>

• AI, Healthcare, Data, Strategy